In the field of data analytics, the analysis of the data is a process of inspecting, cleaning, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, in different business, science, and social science domains.
One tool used in data analytics is known as the “enterprise search.” Enterprise search is the practice of making content from multiple enterprise-type sources, such as databases and intranets, searchable to a defined audience. Enterprise search is used to describe the software of search information within an enterprise (though the search function and its results may still be public). Enterprise search can be contrasted with a web search, which applies search technology to documents on the open web, and a desktop search, which applies search technology to the content on a single computer. The enterprise search focuses on the leveraging value from unstructured text. However, setting up an effective enterprise search strategy is difficult and does not match the consumer search experience on the web.
A newer tool has been developed to address some of the deficiencies of the enterprise search which is referred to herein as the “search oriented business intelligence.” The search oriented business intelligence tool shifts the focus away from unstructured text in favor of structured data. Searches utilizing the search oriented business intelligence tool can target any type of data. Furthermore, advancements in areas, such as natural language processing and deep learning, have improved the search functions beyond simple keyword searches in recent years.
The results of the search oriented business intelligence tool can be made available in either a structured format (e.g., Structured Query Language (SQL), online analytical processing (OLAP), Excel®), a semi-structured format (e.g., Javascript® Object Notation (JSON), Extensible Markup Language (XML)) or an unstructured format.
Hence, the search oriented business intelligence tool allows for better reporting with less data modeling and data preparation.
However, the search oriented business intelligence tool exhibits: poor relevance scoring and results prioritization, incorrect concept and semantic associations that impact filtering and finding related content, limited system of record interfacing, slow to adapt to new types of data, and limited support for web data.
As a result, while the search oriented business intelligence tool allows for better reporting with less data modeling and data preparation, it is deficient in terms of accurately representing the understanding, such as from data scientists, while allowing end users to easily explore and filter data across arbitrary and ad hoc reporting dimensions.